You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
439 lines
14 KiB
Python
439 lines
14 KiB
Python
2 months ago
|
# postgresql/array.py
|
||
|
|
# Copyright (C) 2005-2022 the SQLAlchemy authors and contributors
|
||
|
|
# <see AUTHORS file>
|
||
|
|
#
|
||
|
|
# This module is part of SQLAlchemy and is released under
|
||
|
|
# the MIT License: https://www.opensource.org/licenses/mit-license.php
|
||
|
|
|
||
|
|
import re
|
||
|
|
|
||
|
|
from ... import types as sqltypes
|
||
|
|
from ... import util
|
||
|
|
from ...sql import coercions
|
||
|
|
from ...sql import expression
|
||
|
|
from ...sql import operators
|
||
|
|
from ...sql import roles
|
||
|
|
|
||
|
|
|
||
|
|
def Any(other, arrexpr, operator=operators.eq):
|
||
|
|
"""A synonym for the ARRAY-level :meth:`.ARRAY.Comparator.any` method.
|
||
|
|
See that method for details.
|
||
|
|
|
||
|
|
"""
|
||
|
|
|
||
|
|
return arrexpr.any(other, operator)
|
||
|
|
|
||
|
|
|
||
|
|
def All(other, arrexpr, operator=operators.eq):
|
||
|
|
"""A synonym for the ARRAY-level :meth:`.ARRAY.Comparator.all` method.
|
||
|
|
See that method for details.
|
||
|
|
|
||
|
|
"""
|
||
|
|
|
||
|
|
return arrexpr.all(other, operator)
|
||
|
|
|
||
|
|
|
||
|
|
class array(expression.ClauseList, expression.ColumnElement):
|
||
|
|
|
||
|
|
"""A PostgreSQL ARRAY literal.
|
||
|
|
|
||
|
|
This is used to produce ARRAY literals in SQL expressions, e.g.::
|
||
|
|
|
||
|
|
from sqlalchemy.dialects.postgresql import array
|
||
|
|
from sqlalchemy.dialects import postgresql
|
||
|
|
from sqlalchemy import select, func
|
||
|
|
|
||
|
|
stmt = select(array([1,2]) + array([3,4,5]))
|
||
|
|
|
||
|
|
print(stmt.compile(dialect=postgresql.dialect()))
|
||
|
|
|
||
|
|
Produces the SQL::
|
||
|
|
|
||
|
|
SELECT ARRAY[%(param_1)s, %(param_2)s] ||
|
||
|
|
ARRAY[%(param_3)s, %(param_4)s, %(param_5)s]) AS anon_1
|
||
|
|
|
||
|
|
An instance of :class:`.array` will always have the datatype
|
||
|
|
:class:`_types.ARRAY`. The "inner" type of the array is inferred from
|
||
|
|
the values present, unless the ``type_`` keyword argument is passed::
|
||
|
|
|
||
|
|
array(['foo', 'bar'], type_=CHAR)
|
||
|
|
|
||
|
|
Multidimensional arrays are produced by nesting :class:`.array` constructs.
|
||
|
|
The dimensionality of the final :class:`_types.ARRAY`
|
||
|
|
type is calculated by
|
||
|
|
recursively adding the dimensions of the inner :class:`_types.ARRAY`
|
||
|
|
type::
|
||
|
|
|
||
|
|
stmt = select(
|
||
|
|
array([
|
||
|
|
array([1, 2]), array([3, 4]), array([column('q'), column('x')])
|
||
|
|
])
|
||
|
|
)
|
||
|
|
print(stmt.compile(dialect=postgresql.dialect()))
|
||
|
|
|
||
|
|
Produces::
|
||
|
|
|
||
|
|
SELECT ARRAY[ARRAY[%(param_1)s, %(param_2)s],
|
||
|
|
ARRAY[%(param_3)s, %(param_4)s], ARRAY[q, x]] AS anon_1
|
||
|
|
|
||
|
|
.. versionadded:: 1.3.6 added support for multidimensional array literals
|
||
|
|
|
||
|
|
.. seealso::
|
||
|
|
|
||
|
|
:class:`_postgresql.ARRAY`
|
||
|
|
|
||
|
|
"""
|
||
|
|
|
||
|
|
__visit_name__ = "array"
|
||
|
|
|
||
|
|
stringify_dialect = "postgresql"
|
||
|
|
inherit_cache = True
|
||
|
|
|
||
|
|
def __init__(self, clauses, **kw):
|
||
|
|
clauses = [
|
||
|
|
coercions.expect(roles.ExpressionElementRole, c) for c in clauses
|
||
|
|
]
|
||
|
|
|
||
|
|
super(array, self).__init__(*clauses, **kw)
|
||
|
|
|
||
|
|
self._type_tuple = [arg.type for arg in clauses]
|
||
|
|
main_type = kw.pop(
|
||
|
|
"type_",
|
||
|
|
self._type_tuple[0] if self._type_tuple else sqltypes.NULLTYPE,
|
||
|
|
)
|
||
|
|
|
||
|
|
if isinstance(main_type, ARRAY):
|
||
|
|
self.type = ARRAY(
|
||
|
|
main_type.item_type,
|
||
|
|
dimensions=main_type.dimensions + 1
|
||
|
|
if main_type.dimensions is not None
|
||
|
|
else 2,
|
||
|
|
)
|
||
|
|
else:
|
||
|
|
self.type = ARRAY(main_type)
|
||
|
|
|
||
|
|
@property
|
||
|
|
def _select_iterable(self):
|
||
|
|
return (self,)
|
||
|
|
|
||
|
|
def _bind_param(self, operator, obj, _assume_scalar=False, type_=None):
|
||
|
|
if _assume_scalar or operator is operators.getitem:
|
||
|
|
return expression.BindParameter(
|
||
|
|
None,
|
||
|
|
obj,
|
||
|
|
_compared_to_operator=operator,
|
||
|
|
type_=type_,
|
||
|
|
_compared_to_type=self.type,
|
||
|
|
unique=True,
|
||
|
|
)
|
||
|
|
|
||
|
|
else:
|
||
|
|
return array(
|
||
|
|
[
|
||
|
|
self._bind_param(
|
||
|
|
operator, o, _assume_scalar=True, type_=type_
|
||
|
|
)
|
||
|
|
for o in obj
|
||
|
|
]
|
||
|
|
)
|
||
|
|
|
||
|
|
def self_group(self, against=None):
|
||
|
|
if against in (operators.any_op, operators.all_op, operators.getitem):
|
||
|
|
return expression.Grouping(self)
|
||
|
|
else:
|
||
|
|
return self
|
||
|
|
|
||
|
|
|
||
|
|
CONTAINS = operators.custom_op("@>", precedence=5, is_comparison=True)
|
||
|
|
|
||
|
|
CONTAINED_BY = operators.custom_op("<@", precedence=5, is_comparison=True)
|
||
|
|
|
||
|
|
OVERLAP = operators.custom_op("&&", precedence=5, is_comparison=True)
|
||
|
|
|
||
|
|
|
||
|
|
class ARRAY(sqltypes.ARRAY):
|
||
|
|
|
||
|
|
"""PostgreSQL ARRAY type.
|
||
|
|
|
||
|
|
.. versionchanged:: 1.1 The :class:`_postgresql.ARRAY` type is now
|
||
|
|
a subclass of the core :class:`_types.ARRAY` type.
|
||
|
|
|
||
|
|
The :class:`_postgresql.ARRAY` type is constructed in the same way
|
||
|
|
as the core :class:`_types.ARRAY` type; a member type is required, and a
|
||
|
|
number of dimensions is recommended if the type is to be used for more
|
||
|
|
than one dimension::
|
||
|
|
|
||
|
|
from sqlalchemy.dialects import postgresql
|
||
|
|
|
||
|
|
mytable = Table("mytable", metadata,
|
||
|
|
Column("data", postgresql.ARRAY(Integer, dimensions=2))
|
||
|
|
)
|
||
|
|
|
||
|
|
The :class:`_postgresql.ARRAY` type provides all operations defined on the
|
||
|
|
core :class:`_types.ARRAY` type, including support for "dimensions",
|
||
|
|
indexed access, and simple matching such as
|
||
|
|
:meth:`.types.ARRAY.Comparator.any` and
|
||
|
|
:meth:`.types.ARRAY.Comparator.all`. :class:`_postgresql.ARRAY`
|
||
|
|
class also
|
||
|
|
provides PostgreSQL-specific methods for containment operations, including
|
||
|
|
:meth:`.postgresql.ARRAY.Comparator.contains`
|
||
|
|
:meth:`.postgresql.ARRAY.Comparator.contained_by`, and
|
||
|
|
:meth:`.postgresql.ARRAY.Comparator.overlap`, e.g.::
|
||
|
|
|
||
|
|
mytable.c.data.contains([1, 2])
|
||
|
|
|
||
|
|
The :class:`_postgresql.ARRAY` type may not be supported on all
|
||
|
|
PostgreSQL DBAPIs; it is currently known to work on psycopg2 only.
|
||
|
|
|
||
|
|
Additionally, the :class:`_postgresql.ARRAY`
|
||
|
|
type does not work directly in
|
||
|
|
conjunction with the :class:`.ENUM` type. For a workaround, see the
|
||
|
|
special type at :ref:`postgresql_array_of_enum`.
|
||
|
|
|
||
|
|
.. container:: topic
|
||
|
|
|
||
|
|
**Detecting Changes in ARRAY columns when using the ORM**
|
||
|
|
|
||
|
|
The :class:`_postgresql.ARRAY` type, when used with the SQLAlchemy ORM,
|
||
|
|
does not detect in-place mutations to the array. In order to detect
|
||
|
|
these, the :mod:`sqlalchemy.ext.mutable` extension must be used, using
|
||
|
|
the :class:`.MutableList` class::
|
||
|
|
|
||
|
|
from sqlalchemy.dialects.postgresql import ARRAY
|
||
|
|
from sqlalchemy.ext.mutable import MutableList
|
||
|
|
|
||
|
|
class SomeOrmClass(Base):
|
||
|
|
# ...
|
||
|
|
|
||
|
|
data = Column(MutableList.as_mutable(ARRAY(Integer)))
|
||
|
|
|
||
|
|
This extension will allow "in-place" changes such to the array
|
||
|
|
such as ``.append()`` to produce events which will be detected by the
|
||
|
|
unit of work. Note that changes to elements **inside** the array,
|
||
|
|
including subarrays that are mutated in place, are **not** detected.
|
||
|
|
|
||
|
|
Alternatively, assigning a new array value to an ORM element that
|
||
|
|
replaces the old one will always trigger a change event.
|
||
|
|
|
||
|
|
.. seealso::
|
||
|
|
|
||
|
|
:class:`_types.ARRAY` - base array type
|
||
|
|
|
||
|
|
:class:`_postgresql.array` - produces a literal array value.
|
||
|
|
|
||
|
|
"""
|
||
|
|
|
||
|
|
class Comparator(sqltypes.ARRAY.Comparator):
|
||
|
|
|
||
|
|
"""Define comparison operations for :class:`_types.ARRAY`.
|
||
|
|
|
||
|
|
Note that these operations are in addition to those provided
|
||
|
|
by the base :class:`.types.ARRAY.Comparator` class, including
|
||
|
|
:meth:`.types.ARRAY.Comparator.any` and
|
||
|
|
:meth:`.types.ARRAY.Comparator.all`.
|
||
|
|
|
||
|
|
"""
|
||
|
|
|
||
|
|
def contains(self, other, **kwargs):
|
||
|
|
"""Boolean expression. Test if elements are a superset of the
|
||
|
|
elements of the argument array expression.
|
||
|
|
|
||
|
|
kwargs may be ignored by this operator but are required for API
|
||
|
|
conformance.
|
||
|
|
"""
|
||
|
|
return self.operate(CONTAINS, other, result_type=sqltypes.Boolean)
|
||
|
|
|
||
|
|
def contained_by(self, other):
|
||
|
|
"""Boolean expression. Test if elements are a proper subset of the
|
||
|
|
elements of the argument array expression.
|
||
|
|
"""
|
||
|
|
return self.operate(
|
||
|
|
CONTAINED_BY, other, result_type=sqltypes.Boolean
|
||
|
|
)
|
||
|
|
|
||
|
|
def overlap(self, other):
|
||
|
|
"""Boolean expression. Test if array has elements in common with
|
||
|
|
an argument array expression.
|
||
|
|
"""
|
||
|
|
return self.operate(OVERLAP, other, result_type=sqltypes.Boolean)
|
||
|
|
|
||
|
|
comparator_factory = Comparator
|
||
|
|
|
||
|
|
def __init__(
|
||
|
|
self, item_type, as_tuple=False, dimensions=None, zero_indexes=False
|
||
|
|
):
|
||
|
|
"""Construct an ARRAY.
|
||
|
|
|
||
|
|
E.g.::
|
||
|
|
|
||
|
|
Column('myarray', ARRAY(Integer))
|
||
|
|
|
||
|
|
Arguments are:
|
||
|
|
|
||
|
|
:param item_type: The data type of items of this array. Note that
|
||
|
|
dimensionality is irrelevant here, so multi-dimensional arrays like
|
||
|
|
``INTEGER[][]``, are constructed as ``ARRAY(Integer)``, not as
|
||
|
|
``ARRAY(ARRAY(Integer))`` or such.
|
||
|
|
|
||
|
|
:param as_tuple=False: Specify whether return results
|
||
|
|
should be converted to tuples from lists. DBAPIs such
|
||
|
|
as psycopg2 return lists by default. When tuples are
|
||
|
|
returned, the results are hashable.
|
||
|
|
|
||
|
|
:param dimensions: if non-None, the ARRAY will assume a fixed
|
||
|
|
number of dimensions. This will cause the DDL emitted for this
|
||
|
|
ARRAY to include the exact number of bracket clauses ``[]``,
|
||
|
|
and will also optimize the performance of the type overall.
|
||
|
|
Note that PG arrays are always implicitly "non-dimensioned",
|
||
|
|
meaning they can store any number of dimensions no matter how
|
||
|
|
they were declared.
|
||
|
|
|
||
|
|
:param zero_indexes=False: when True, index values will be converted
|
||
|
|
between Python zero-based and PostgreSQL one-based indexes, e.g.
|
||
|
|
a value of one will be added to all index values before passing
|
||
|
|
to the database.
|
||
|
|
|
||
|
|
.. versionadded:: 0.9.5
|
||
|
|
|
||
|
|
|
||
|
|
"""
|
||
|
|
if isinstance(item_type, ARRAY):
|
||
|
|
raise ValueError(
|
||
|
|
"Do not nest ARRAY types; ARRAY(basetype) "
|
||
|
|
"handles multi-dimensional arrays of basetype"
|
||
|
|
)
|
||
|
|
if isinstance(item_type, type):
|
||
|
|
item_type = item_type()
|
||
|
|
self.item_type = item_type
|
||
|
|
self.as_tuple = as_tuple
|
||
|
|
self.dimensions = dimensions
|
||
|
|
self.zero_indexes = zero_indexes
|
||
|
|
|
||
|
|
@property
|
||
|
|
def hashable(self):
|
||
|
|
return self.as_tuple
|
||
|
|
|
||
|
|
@property
|
||
|
|
def python_type(self):
|
||
|
|
return list
|
||
|
|
|
||
|
|
def compare_values(self, x, y):
|
||
|
|
return x == y
|
||
|
|
|
||
|
|
def _proc_array(self, arr, itemproc, dim, collection):
|
||
|
|
if dim is None:
|
||
|
|
arr = list(arr)
|
||
|
|
if (
|
||
|
|
dim == 1
|
||
|
|
or dim is None
|
||
|
|
and (
|
||
|
|
# this has to be (list, tuple), or at least
|
||
|
|
# not hasattr('__iter__'), since Py3K strings
|
||
|
|
# etc. have __iter__
|
||
|
|
not arr
|
||
|
|
or not isinstance(arr[0], (list, tuple))
|
||
|
|
)
|
||
|
|
):
|
||
|
|
if itemproc:
|
||
|
|
return collection(itemproc(x) for x in arr)
|
||
|
|
else:
|
||
|
|
return collection(arr)
|
||
|
|
else:
|
||
|
|
return collection(
|
||
|
|
self._proc_array(
|
||
|
|
x,
|
||
|
|
itemproc,
|
||
|
|
dim - 1 if dim is not None else None,
|
||
|
|
collection,
|
||
|
|
)
|
||
|
|
for x in arr
|
||
|
|
)
|
||
|
|
|
||
|
|
@util.memoized_property
|
||
|
|
def _against_native_enum(self):
|
||
|
|
return (
|
||
|
|
isinstance(self.item_type, sqltypes.Enum)
|
||
|
|
and self.item_type.native_enum
|
||
|
|
)
|
||
|
|
|
||
|
|
def bind_expression(self, bindvalue):
|
||
|
|
return bindvalue
|
||
|
|
|
||
|
|
def bind_processor(self, dialect):
|
||
|
|
item_proc = self.item_type.dialect_impl(dialect).bind_processor(
|
||
|
|
dialect
|
||
|
|
)
|
||
|
|
|
||
|
|
def process(value):
|
||
|
|
if value is None:
|
||
|
|
return value
|
||
|
|
else:
|
||
|
|
return self._proc_array(
|
||
|
|
value, item_proc, self.dimensions, list
|
||
|
|
)
|
||
|
|
|
||
|
|
return process
|
||
|
|
|
||
|
|
def result_processor(self, dialect, coltype):
|
||
|
|
item_proc = self.item_type.dialect_impl(dialect).result_processor(
|
||
|
|
dialect, coltype
|
||
|
|
)
|
||
|
|
|
||
|
|
def process(value):
|
||
|
|
if value is None:
|
||
|
|
return value
|
||
|
|
else:
|
||
|
|
return self._proc_array(
|
||
|
|
value,
|
||
|
|
item_proc,
|
||
|
|
self.dimensions,
|
||
|
|
tuple if self.as_tuple else list,
|
||
|
|
)
|
||
|
|
|
||
|
|
if self._against_native_enum:
|
||
|
|
super_rp = process
|
||
|
|
pattern = re.compile(r"^{(.*)}$")
|
||
|
|
|
||
|
|
def handle_raw_string(value):
|
||
|
|
inner = pattern.match(value).group(1)
|
||
|
|
return _split_enum_values(inner)
|
||
|
|
|
||
|
|
def process(value):
|
||
|
|
if value is None:
|
||
|
|
return value
|
||
|
|
# isinstance(value, util.string_types) is required to handle
|
||
|
|
# the case where a TypeDecorator for and Array of Enum is
|
||
|
|
# used like was required in sa < 1.3.17
|
||
|
|
return super_rp(
|
||
|
|
handle_raw_string(value)
|
||
|
|
if isinstance(value, util.string_types)
|
||
|
|
else value
|
||
|
|
)
|
||
|
|
|
||
|
|
return process
|
||
|
|
|
||
|
|
|
||
|
|
def _split_enum_values(array_string):
|
||
|
|
|
||
|
|
if '"' not in array_string:
|
||
|
|
# no escape char is present so it can just split on the comma
|
||
|
|
return array_string.split(",") if array_string else []
|
||
|
|
|
||
|
|
# handles quoted strings from:
|
||
|
|
# r'abc,"quoted","also\\\\quoted", "quoted, comma", "esc \" quot", qpr'
|
||
|
|
# returns
|
||
|
|
# ['abc', 'quoted', 'also\\quoted', 'quoted, comma', 'esc " quot', 'qpr']
|
||
|
|
text = array_string.replace(r"\"", "_$ESC_QUOTE$_")
|
||
|
|
text = text.replace(r"\\", "\\")
|
||
|
|
result = []
|
||
|
|
on_quotes = re.split(r'(")', text)
|
||
|
|
in_quotes = False
|
||
|
|
for tok in on_quotes:
|
||
|
|
if tok == '"':
|
||
|
|
in_quotes = not in_quotes
|
||
|
|
elif in_quotes:
|
||
|
|
result.append(tok.replace("_$ESC_QUOTE$_", '"'))
|
||
|
|
else:
|
||
|
|
result.extend(re.findall(r"([^\s,]+),?", tok))
|
||
|
|
return result
|